“…Through active participatory use and negotiation to exploit the existing rules of the algorithm, users as actors try to change the original logic of algorithmic output ( Clark, 2020 ),violate the “original” meanings set by the algorithm and finally create diverse meanings to meet their usage purposes ( Eslami et al, 2016 ; Ettlinger, 2018 ; Velkova and Kaun, 2021 ). Driven by this concept, a number of studies have explored diverse forms of algorithmic resistance among social media users, such as attempting to domesticate algorithms using social media content recommendation rules ( Sujon et al, 2018 ; Leong, 2020 ; Siles et al, 2020 ); utilizing algorithmic ranking rules to make the content one wants to display weight up to become “visible” ( Velkova and Kaun, 2021 ); “teasing” and “confusing” the TikTok algorithm by changing personal preference settings to achieve “unexpected” recommendation visibility effects ( Cotter, 2019 ), fighting against recommendation algorithms’ discrimination toward marginalized groups by frequently adjusting identity privilege settings ( Mittmann et al, 2021 ), and so on. Nevertheless, the above-mentioned studies on algorithmic resistance still have some shortcomings, which leave some space for expansion in this study.…”